Crimes are rampant in many locations and countries nowadays. To attack this problem, monitoring systems are widely set up in recent years in public and private sites. For instance, most railways or high speed trains now adopt computerized automatic driving. In such autopilot public transportation systems, occurrence of obstacles on the routes is the greatest safety concern. Or in some important public sites, such as art galleries, museums, government organizations and the like, to prevent theft or disposing of unknown articles (such as explosives), a lot of manpower has to be deployed to do monitoring, or expensive theft-thwarting equipments have to be installed. To crack down traffic violations on roads, policemen have to drive hauling vehicles to do patrolling. Thus a great deal of human resources and precious time are wasted. An intelligent monitoring system is able to identify selected events and activities such as presence of obstacles, vehicle violations or thefts, and capable of instantly notifying related people or generating alarm would be very helpful.
Conventional monitoring techniques often focus on object image segmentation or tracking, and comparison. System test films mostly adopt academic standard films without taking into account of actual environments. Hence how to establish backgrounds and update background information often are neglected. As an actual background often involves constantly moving objects, there is no idle duration allowing the system to capture the background, or a period of training is needed to generate the background.
Moreover, most conventional techniques do not provide comprehensive exploration on static objects. For instance, National Taiwan University provides a “Background Registration” technique capable of detecting objects. It has a drawback, namely once a judgment is made, a background is saved, the saved background data remains unchanged without updated.
Another conventional technique is Codebook system. It provides background learning and an image detection method. In the event that an object is static, it becomes a background. However, if the static object is an explosive and becomes the background of the monitoring system, the purpose of monitoring is futile.
The two conventional approaches mentioned above still have rooms for improvement, notably: 1. No update of the background does not meet actual requirement; 2. Objects in actual sites are not always dynamic; a neglected static object should be updated to become a background (such as a vehicle parked on a road side, trash dropped on the ground by people, or the like). There are other conventional techniques that can update static objects to become the background. But the update speed is a constraint. As a result, the conventional monitoring systems still leave a lot to be desired.